AI chatbots, LLM apps and generative-AI integration for Indian businesses
SubhSync Technologies builds production-ready AI chatbots, RAG-powered knowledge assistants, voice-AI agents and LLM-integrated apps for Indian and global businesses. We've shipped chatbots that handle thousands of conversations per day, internal copilots that save sales teams 15+ hours per week, and voice-AI agents that qualify inbound calls 24×7.
We don't sell hype — we ship measurable AI products. Every project starts with the question: "What metric will this AI improve, and by how much?"
AI products we build
1. Customer-support AI chatbots (RAG)
Trained on your help docs, FAQs, product manuals and past support tickets. Answers 60–80% of common queries without human involvement, with cited sources.
- Ingest from PDFs, Notion, Confluence, Zendesk, Intercom, Google Drive, websites or any database.
- Chunked, embedded and indexed into a vector database (Pinecone, Weaviate, pgvector, Qdrant).
- Conversation memory across sessions, multi-turn context, follow-up question handling.
- Citations with deep-links to the source document/page.
- Escalation to human agents (Zendesk, Freshdesk, Intercom, Crisp) with full transcript.
- Languages: English, Hindi, Tamil, Telugu, Bengali, Marathi, Gujarati and 90+ more.
2. Lead-generation & qualification chatbots
- Replaces "Contact us" forms — qualifies leads through natural conversation.
- Captures name, email, phone, budget, timeline and intent — pushes to your CRM.
- Books meetings into Calendly / Cal.com / Google Calendar automatically.
- Integrates with HubSpot, Zoho CRM, Salesforce, Pipedrive, Freshsales.
3. WhatsApp Business chatbots
- Meta WhatsApp Business Cloud API (official), Gupshup, AiSensy, Wati, Interakt.
- Template message approval, opt-in workflows, 24-hour-window handling.
- Order tracking, abandoned-cart recovery, appointment reminders, payment links.
- Full conversational AI on top of templates — not just rule-based menus.
4. Voice-AI agents (inbound & outbound calls)
- 24×7 inbound voice agents that qualify leads, book appointments, answer FAQs.
- Outbound campaigns — surveys, feedback, payment reminders, lead nurturing.
- Built on Vapi, Retell AI, ElevenLabs Conversational AI, OpenAI Realtime API or LiveKit.
- Indian English, Hindi, Hinglish and major regional language voices.
- Integration with telephony (Twilio, Plivo, Exotel, Knowlarity, MyOperator).
5. Internal AI copilots
- Sales copilot — drafts emails, summarises calls, suggests next-best-action.
- Support copilot — drafts replies, suggests articles, summarises long tickets.
- HR copilot — answers policy questions, drafts JDs, screens resumes.
- Engineering copilot — searches internal docs, runbooks, postmortems.
- Slack-bot, Teams-bot or web-app delivery.
6. Document intelligence & AI agents
- Invoice / PO / contract extraction with structured JSON output.
- KYC document parsing and validation.
- Multi-step AI agents that use tools (search the web, query DBs, send emails, run code).
- Built with LangGraph, LlamaIndex Agents, OpenAI Assistants, AutoGen.
7. Custom LLM features inside your existing app
- "Ask AI" search bars over your product data.
- AI-generated summaries, suggestions, classifications.
- Smart autocomplete, content rewriting, translation.
- Prompt engineering, function-calling, structured-output JSON, streaming UX.
AI tech stack
- Models: OpenAI (GPT-4o, GPT-4.1, o3, o3-mini), Anthropic Claude 3.5 Sonnet / Opus, Google Gemini 1.5 Pro / 2.0 Flash, Meta Llama 3.3, Mistral Large, Qwen 2.5, DeepSeek V3.
- Frameworks: LangChain, LangGraph, LlamaIndex, Vercel AI SDK, Haystack, Semantic Kernel.
- Vector DBs: Pinecone, Weaviate, Qdrant, pgvector, Milvus, Chroma.
- Voice: Vapi, Retell AI, ElevenLabs, Deepgram, Whisper, OpenAI Realtime, LiveKit.
- Self-hosted LLMs: vLLM, Ollama, Together AI, Groq, Fireworks for low-latency / private deployments.
- Eval & observability: LangSmith, Langfuse, Helicone, Phoenix, Braintrust.
AI chatbot pricing in India
| Project type | Timeline | Starting price (INR) |
|---|---|---|
| FAQ chatbot trained on your website | 5–7 days | ₹5,000 |
| RAG chatbot with private docs + CRM hand-off | 2–3 weeks | ₹40,000 |
| WhatsApp Business AI chatbot | 3–4 weeks | ₹60,000 |
| Voice-AI inbound agent | 4–6 weeks | ₹2,00,000 |
| Internal copilot (sales / support / HR) | 4–8 weeks | ₹2,50,000 |
| Multi-agent AI workflow / document intelligence | 6–10 weeks | ₹3,50,000 |
LLM API usage (OpenAI, Gemini, Claude) is billed at cost — typically ₹2,000–₹20,000/month depending on volume.
Why work with us on AI?
- We build shipped, measured AI products — not demos that only work in a screenshot.
- Hallucination-aware design: grounding, citations, confidence thresholds, eval harnesses.
- Vendor-neutral — we'll switch you from OpenAI to Gemini to Claude based on cost/quality, not bias.
- Production-grade observability so you can see every conversation, token, latency and cost.
- You own the code, embeddings, vector DB and conversation logs.
Talk to an AI engineer
Bring your messiest data or your trickiest workflow — we'll tell you in 30 minutes whether AI is the right tool, what it'll cost, and what success will look like.
Frequently asked questions
What kinds of AI chatbots do you build?
We build customer-support bots (trained on your help docs and FAQs), lead-generation and qualification bots, internal AI copilots for sales/ops/HR teams, voice-AI agents for inbound calls, and WhatsApp Business chatbots integrated with your CRM.
Which LLM models do you use?
We choose the right model per use case: OpenAI (GPT-4o, GPT-4.1, o3) for complex reasoning, Google Gemini 1.5 Pro / 2.0 Flash for long-context and multimodal, Anthropic Claude 3.5 Sonnet for nuanced writing and code, and open-source models (Llama 3.3, Mistral, Qwen) when self-hosting is required for cost or privacy.
How much does an AI chatbot cost in India?
A basic FAQ chatbot trained on your website starts at ₹5,000. A RAG chatbot with custom data ingestion, conversation memory and CRM integration starts at ₹40,000. Voice-AI agents and full enterprise rollouts start at ₹2,00,000. LLM API usage is billed at cost.
Can the chatbot learn from our private documents (RAG)?
Yes. We implement Retrieval Augmented Generation: we ingest your PDFs, Notion/Confluence pages, websites, Google Docs, Zendesk articles or databases, chunk and embed them into a vector database (Pinecone, Weaviate, pgvector or Qdrant), and the LLM answers using only your verified content with citations.
Will the bot work on WhatsApp?
Yes. We integrate via Meta's WhatsApp Business Cloud API, Gupshup, AiSensy or Wati. We handle template message approvals, opt-in workflows and the 24-hour customer service window.
Can it hand off to a human agent when needed?
Yes. We build escalation rules (low confidence, sentiment, keyword triggers, customer request) that hand off to your human agents on Zendesk, Freshdesk, Intercom, Crisp or Slack — with the full conversation history attached.
How do you prevent hallucinations and brand-safety issues?
We constrain the bot with a strict system prompt, force grounding on your retrieved documents, add output guardrails (toxicity, PII, off-topic detection), set conservative temperature, and log every conversation for review. For high-stakes use cases we add a confidence threshold + human-in-the-loop.
Do we own the chatbot and data?
Yes. The code lives in your GitHub, the vector DB and embeddings live in your cloud account, and conversation logs are in your database. You can switch LLM providers at any time without losing data.